20 citations · 46 across the 15 of their papers we have counts for
7 papers · 1 filter
Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty
Zikun Lin, Daniel Zhuoyu Long, Viet Anh Nguyen
Ambulance response is time-critical in out-of-hospital cardiac arrest (OHCA), where dispatchers must balance timely arrivals with limited fleet capacity. Static territories and det…
Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints
Jiajin Li, Sirui Lin, Jose Blanchet +1
Distributionally robust optimization has been shown to offer a principled way to regularize learning models. In this paper, we find that Tikhonov regularization is distributionally…
Principal Component Hierarchy for Sparse Quadratic Programs
Robbie Vreugdenhil, Viet Anh Nguyen, Armin Eftekhari +1
We propose a novel approximation hierarchy for cardinality-constrained, convex quadratic programs that exploits the rank-dominating eigenvectors of the quadratic matrix. Each level…
Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization
Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Daniel Kuhn +1
We introduce a distributionally robust minimium mean square error estimation model with a Wasserstein ambiguity set to recover an unknown signal from a noisy observation. The propo…
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization
Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Man-Chung Yue +2
A fundamental problem arising in many areas of machine learning is the evaluation of the likelihood of a given observation under different nominal distributions. Frequently, these…
Wasserstein Distributionally Robust Kalman Filtering
Soroosh Shafieezadeh-Abadeh, Viet Anh Nguyen, Daniel Kuhn +1
We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions. We show that the optimal es…